J.T. Fluharty-Jaidee
Feb 2, 2021
We can use some detailed forecasting, but this is better left to the macro-economist. That is after all… what they get paid to do. So let's not re-work their jobs, instead use (i.e. read) what they produce.
Each year the IMF produces the World Economic Outlook report.
As with most macro-economic reports we are focused on economic activity. That can be interpreted through estimations of GDP growth, inflation and 'economic indicators'. Note that 'output' means GDP.
Some key notes we can see from the information presented in the graphics:
China had a quick dip and has returned to their steady-state growth path. (8.75% p.a. growth)
Emerging markets and Advanced Economies (i.e. US, Britain, much of Europe, Russia, and Japan) suffered significantly worse and will not recover to prior projections.
Chinese investment has more than recovered, others have not.
Industrial production globally recovered quickly
Bankruptcies, globally, are actually down compared to other recessions (probably due to moratoriums and stimulus.) (This is great!)
The OECD provides a wealth of economic forecasts and data as well as charts you can sort and play around with. With very little work you can gain an understanding of what is going on globally.
Similar to the above two, the World Bank and Federal Reserve have a wealth of information on their sites:
Again, here we are attempting to just determine what are the global directions things are headed. Global macro-economics are extremely complex (and integrated) and so forecasting is itself extremely difficult to pull off with any level of accuracy. Best to leave it to the pros on this one.
You've just completed your global macro-economic trends analysis. You have a firm grasp of where things are headed.
The next step is to select sectors that are expected to out-perform within each country. For this discussion we should be looking at China (i.e. invest where the growth is). But since much of that information is not in English, we will use America. Application is the same.
The next question becomes which sectors should we invest in?
Q: How to know?
A: Plot long-run sector fund returns (sector ETFs) and see what is going on.
At the time of this writing, we can see a few sectors that stick out even if we change the time window:
Many of these have even significantly outperformed the SPY in recent years. These sectors are growing, we should allocate more of our portfolio to stocks which exist within these sectors (or buy the ETFs themselves).
After determining what sectors you want to be invested in (and what country), you can screen for stocks on some basic knock out conditions from simple finance:
Clearing out the bad firms–you are left with firms to investigate.
An easy screener to use is Yahoo Finance's screener, but you can use Bloomberg, Reuters, Koyfin, etc.
As the case discusses, there are two types of financial analysis one may use in choosing to invest in a particular firm:
Technical Analysis is often called 'charting'. The technique does take some practice and it is often wrong.
Fundamental Analysis falls into two major categories:
\[ FCF = EBIT(1-t)+D\&A - CAPEX - \Delta NOWC \]
or
\[ FCF = NOPAT - \Delta PP\&E - \Delta NOWC \]
Discounting given a risk-rate gets you the firm's value:
\[ V_{firm} = \frac{FCF_1}{(1+r)^{1}}+\frac{FCF_2}{(1+r)^{2}}+\dots+\frac{FCF_n+Terminal}{(1+r)^{n}} \]
Note: \( V_{firm} \) is nearly identical to NPV. (This is important.)
Once you have found the firm's value you can find its intrinsic price/value per share:
\[ P_v = \frac{V_{firm}}{shares\ outstanding} \]
\( P_v \geq P_m \), value is higher than price in the market, buy the asset.
\( P_v < P_m \), value is lower than price in the market, do not buy (sell).
(Hint: rules are the same as NPV.)
Download or use full screen at the bottom right.
Comparables assume that markets are efficient (EMH). If markets are efficient, then the value of one firm is equivalent in proportion to other firms.
Some of the most common comparables (valuation metrics) are:
To do a comparables analysis, you need to identify other 'like' firms to the one you are attempting to value. For example, suppose we were attempting to value Kroger (KR).
| Symbol | Price.Sales | Price.Book | Div.Share | Forward.P.E | PEG.Ratio | Shares.Out | EPS | Last.Price | Avg.Vol |
|---|---|---|---|---|---|---|---|---|---|
| AMZN | 4.31 | 17.8 | 0 | 49.71 | 1.71 | 500.89M | 41.83 | 3305 | 3.861M |
| TGT | 1.1 | 7.3 | 2.66 | 22.36 | 1.48 | 500.773M | 7.54 | 194.29 | 4.037M |
| ACI | 0.11 | - | 0.1 | - | 0.31 | 465.533M | - | 16.75 | 2.657M |
| COST | 0.92 | 10.72 | 2.75 | 32.63 | 4.16 | 442.955M | 9.74 | 359.56 | 2.458M |
| ADRNY | - | 1.9 | 0.96 | 16.66 | - | 1.043B | 1.94 | 27.99 | 149359 |
| WMT | 0.75 | 5.07 | 2.15 | 25.45 | 3.76 | 2.829B | 6.93 | 145.83 | 7.617M |
| ——— | ——— | ——— | ——— | ——— | ——— | ——— | ——— | ——— | ——— |
| Avg. | 1.44 | 8.56 | 1.44 | 29.36 | 2.28 | 13.60 | |||
| ——— | ——— | ——— | ——— | ——— | ——— | ——— | ——— | ——— | ——— |
| KR | 0.2 | 2.56 | 0.66 | 12.53 | 1.23 | 761.347M | 3.74 | 33.59 | 12.842M |
Having collected these comparables we find the average of the metrics, and using Kroger's data we can back out what the price of the stock should be. For example we know that the average Forward P/E was 29.36, so we can estimate Kroger's price using their EPS of $3.74 to be:
\[ P/E_{Comp} \times Earnings_{Kroger} = Price_{Kroger} \]
\[ 29.36 \times \$3.74 = \$109.80 \]
Since Kroger's current share price is $33.59, this is quite a ways off. Generally you will want to use quite a few comparables and take an average of the result. Also, you want to do your best to pick truly comparable companies. I.e…. is Amazon comparable/like/similar?
Despite being extremely error prone, imprecise, and assuming efficient markets, comparables are used excessively by the following:
My personal opinion—fun to look at, but discount the result heavily (i.e. don't trust it).
Let's suppose you choose your investments after doing your comparables and DCF and financial statement analysis so you know all of what you would like to invest in and whittled down the filter set to 40 or so 'good' companies.
First, plot your possible investments together.
\[ wealth_t = \$1 \prod_{t=1}^T (1+r_t) \]
\( \prod_{t=1}^T (1+r_t) = (1+r_1)(1+r_2)(1+r_3)\dots(1+r_T) \)
MSFT TSM NVDA ACN TXN AMAT LRCX KLIC
INFY INTU AMD SAP ACLS LUNA INVA
After plotting them you may notice that some of your 'great picks' under-perform:
They may not be well known.
Make the selection of firms you want to include. Be sure not to overweight one sector.
Next, naturally you want to be choosing investments which work well together in a portfolio. Having just chosen 'good' investments that have either strong value or growth prospects you can move to the optimization stage.
This will attempt to do the following:
Portfolio optimization is also a selection tool. A phenomenal stock that ruins a portfolio's risk prospects should never be included.
Portfolio optimization is simply a way to select the highest return subject to risk that you can achieve given all the possible weights of assets in your portfolio.
The portfolio with the highest return to risk ratio will have the highest Sharpe:
\[ Sharpe\ Ratio = \frac{E(r_p)-r_f}{\sigma_p} \approx \frac{Excess\ Return}{Risk} \]
So the 'Tangency portfolio' is the one with the highest Sharpe and is also optimal.
If markets are efficient, the tangency portfolio is also the market portfolio.
This is why the case mentions passive and active investors.
If you go through the selection process, and markets are efficient—then you are better off simply holding the market portfolio.
If markets are not efficient, then you may be able to out-perform, by making superior selections and having a better portfolio. (Active Investing)
Assuming you fall on the side of Puglia and not Buffett – and you want any sort of job in finance – you have to be willing to accept that markets are not forever and always efficient.
Assuming you agree that markets are not always efficient, or you are naive enough to hope to beat the market. You plan to optimize your selection. Yes, we could use a lot of math…
\[ \min_{w_1,w_2,\dots,w_n} \boldsymbol{w}\boldsymbol{\varOmega}\boldsymbol{w'} \]
\[ s.t.\ \ \boldsymbol{r'}\boldsymbol{w} \]
\[ \sigma^2_{p_5}= \boldsymbol{w}\boldsymbol{\varOmega}\boldsymbol{w'} = \begin{bmatrix} w_1 & w_2 & w_3 & w_4 & w_5 \end{bmatrix} \begin{bmatrix} \sigma^2_1 & \sigma_{1,2} & \sigma_{1,3} & \sigma_{1,4} & \sigma_{1,5} \\ \sigma_{2,1} & \sigma^2_2& \sigma_{2,3} & \sigma_{2,4} & \sigma_{2,5} \\ \sigma_{3,1} & \sigma_{3,2} & \sigma^2_3 & \sigma_{3,4} & \sigma_{3,5} \\ \sigma_{4,1} & \sigma_{4,2} & \sigma_{4,3} &\sigma^2_4 & \sigma_{4,5} \\ \sigma_{5,1} & \sigma_{5,2} & \sigma_{5,3} & \sigma_{5,4} & \sigma^2_5 \\ \end{bmatrix} \begin{bmatrix} w_1 \\ w_2 \\ w_3 \\ w_4 \\ w_5 \end{bmatrix} \]
Or…. use a website and let it do it for us.
And you may end up out-performing the market… but nobody asked me.
After you set up your portfolio which may or may not out perform the market already. Perhaps go a step further and learn to hedge with derivatives.
1.When the macro-economics indicate the market will drop.
2.Yes, you can do some complicated hedging too…see Hibbert or Kurov about it.